#python ../preprocess.py -train_src rawdata/train_sources -train_tgt rawdata/train_targets -valid_src rawdata/valid_sources -valid_tgt rawdata/valid_targets -src_vocab rawdata/vocab -tgt_vocab rawdata/vocab -save_data data/rs

NUM=0
TRAIN=./train/$NUM
if [ ! -d $TRAIN ];then
	mkdir $TRAIN
fi

#python ../train.py \
#       	-data data/rs \
#	-train_from $TRAIN/rs_step_21700.pt \
#	-train_steps 200000 \
#       	-valid_steps 500 \
#	-save_checkpoint_steps 500 \
#	-save_model $TRAIN/rs \
#	-layers 4 \
#	-rnn_size 128 \
#	-word_vec_size 128 \
#	-max_grad_norm 0 \
#	-optim adam \
#	-encoder_type transformer \
#	-decoder_type transformer \
#       	-dropout 0.2 \
#	-param_init 0 \
#	-warmup_steps 2000 \
#	-position_encoding \
#	-learning_rate 0.05 \
#	-decay_method noam \
#	-gpu_ranks 0 -world_size 1 \
#	-tensorboard \
#	-tensorboard_log_dir $TRAIN
#

STEP=36500
python ../translate.py -model $TRAIN/rs_step_$STEP.pt -src rawdata/test_sources -output $TRAIN/test_targets_  -batch_size 1000 -gpu 0 -replace_unk -verbose
